Paul Schafran Jacobs

EECS Department, University of California, Berkeley

Technical Report No. UCB/CSD-86-254

, 1986

http://www2.eecs.berkeley.edu/Pubs/TechRpts/1986/CSD-86-254.pdf

The development of natural language interfaces to Artificial Intelligence systems is dependent on the representation of knowledge. A major impediment to building such systems has been the difficulty in adding sufficient linguistic and conceptual knowledge to extend and adapt their capabilities. This difficulty has been apparent in systems which perform the task of language production, <i>i. e.</i> the generation of natural language output to satisfy the communicative requirements of a system. <p> The problem of extending and adapting linguistic capabilities is rooted in the problem of integrating abstract and specialized knowledge and applying this knowledge to the language processing task. Three aspects of a knowledge representation system are highlighted by this problem: hierarchy, or the ability to represent relationships between abstract and specific knowledge structures; explicit referential knowledge, or knowledge about relationships among concepts used in referring to concepts; and uniformity, the use of a common framework for linguistic and conceptual knowledge. The knowledge-based approach to language production addresses the language generation task from within the broader context of the representation and application of conceptual and linguistic knowledge. <p> This knowledge-based approach has led to the design and implementation of a knowledge representation framework, called Ace, geared towards facilitating the interaction of linguistic and conceptual knowledge in language processing. Ace is a uniform, hierarchical representation system, which facilitates the use of abstractions in the encoding of specialized knowledge and the representation of the referential and metaphorical relationships among concepts. <p> A general-purpose natural language generator, KING (Knowledge INtensive Generator), has been implemented to apply knowledge in the Ace form. The generator is designed for knowledge-intensivity and incrementality, to exploit the power of the Ace knowledge in generation. The generator works by applying structured associations, or mappings, from conceptual to linguistic structures, and combining these structures into grammatical utterances. This has proven to be a simple but powerful mechanism, easy to adapt and extend, and has provided strong support for the role of conceptual organization in language generation.

Advisors: Robert Wilensky

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BibTeX citation:

@phdthesis{Jacobs:CSD-86-254,
    Author= {Jacobs, Paul Schafran},
    Title= {A Knowledge-Based Approach to Language Production},
    School= {EECS Department, University of California, Berkeley},
    Year= {1986},
    Month= {Aug},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/1986/6082.html},
    Number= {UCB/CSD-86-254},
    Abstract= {The development of natural language interfaces to Artificial Intelligence systems is dependent on the representation of knowledge. A major impediment to building such systems has been the difficulty in adding sufficient linguistic and conceptual knowledge to extend and adapt their capabilities. This difficulty has been apparent in systems which perform the task of language production, <i>i. e.</i> the generation of natural language output to satisfy the communicative requirements of a system.  <p>  The problem of extending and adapting linguistic capabilities is rooted in the problem of integrating abstract and specialized knowledge and applying this knowledge to the language processing task. Three aspects of a knowledge representation system are highlighted by this problem: hierarchy, or the ability to represent relationships between abstract and specific knowledge structures; explicit referential knowledge, or knowledge about relationships among concepts used in referring to concepts; and uniformity, the use of a common framework for linguistic and conceptual knowledge. The knowledge-based approach to language production addresses the language generation task from within the broader context of the representation and application of conceptual and linguistic knowledge.  <p>  This knowledge-based approach has led to the design and implementation of a knowledge representation framework, called Ace, geared towards facilitating the interaction of linguistic and conceptual knowledge in language processing. Ace is a uniform, hierarchical representation system, which facilitates the use of abstractions in the encoding of specialized knowledge and the representation of the referential and metaphorical relationships among concepts.  <p>  A general-purpose natural language generator, KING (Knowledge INtensive Generator), has been implemented to apply knowledge in the Ace form. The generator is designed for knowledge-intensivity and incrementality, to exploit the power of the Ace knowledge in generation. The generator works by applying structured associations, or mappings, from conceptual to linguistic structures, and combining these structures into grammatical utterances. This has proven to be a simple but powerful mechanism, easy to adapt and extend, and has provided strong support for the role of conceptual organization in language generation.},
}

EndNote citation:

%0 Thesis
%A Jacobs, Paul Schafran 
%T A Knowledge-Based Approach to Language Production
%I EECS Department, University of California, Berkeley
%D 1986
%@ UCB/CSD-86-254
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/1986/6082.html
%F Jacobs:CSD-86-254